Generating rules to automatically extract linguistic patterns from documents is provided. A first plurality of linguistic pattern extraction rules corresponding to a user-selected text example from a document is generated according to a first abstraction rule of a plurality of abstraction rules. Each respective linguistic pattern extraction rule of the first plurality of linguistic pattern extraction rules having a first identified level of abstraction. The first plurality of linguistic pattern extraction rules ordered by the first identified level of abstraction is presented in a first list to a user via a user interface. A selection of one particular linguistic pattern extraction rule is received from the first list by the user via the user interface. That one particular linguistic pattern extraction rule selected by the user is applied to the document to automatically extract user-desired linguistic patterns similar to the user-selected text example from the document.
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6. The computer-implemented method of claim 5, wherein the first abstraction rule abstracts a set of tokens corresponding to the user-selected text example based on at least one of a user dictionary or defined parts of speech, and wherein the second abstraction rule abstracts a particular type of token corresponding to the user-selected text example a defined number of times, and wherein the third abstraction rule abstracts tokens corresponding to the user-selected text example based on heuristics.
7. The computer-implemented method of claim 5, wherein each respective linguistic pattern extraction rule has a corresponding rule abstraction score that is based on a sum of token abstraction scores of a set of tokens in a given linguistic pattern extraction rule for ordering linguistic pattern extraction rules in a given list.
9. The computer-implemented method of claim 1, wherein the computer annotates or highlights linguistic patterns extracted from documents.
20. The computer program product of claim 19, wherein the first abstraction rule abstracts a set of tokens corresponding to the user-selected text example based on at least one of a user dictionary or defined parts of speech, and wherein the second abstraction rule abstracts a particular type of token corresponding to the user-selected text example a defined number of times, and wherein the third abstraction rule abstracts tokens corresponding to the user-selected text example based on heuristics.
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June 21, 2021
November 1, 2022
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